{"id":"W4242878675","doi":"10.1515/iupac.79.1645","title":"Morbidity Survey","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Health Promotion and Cardiovascular Prevention","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Glossary; Chemical nomenclature; Multidisciplinary approach; Hazard; Computer science; Toxicology; Library science; Chemistry; Philosophy; Biology; Sociology; Social science; Linguistics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001147353,0.001080386,0.001518915,0.003962061,0.0005603138,0.001490533,0.001775098,0.001206195,0.06473944],"category_scores_gemma":[0.01091637,0.0004072995,0.001994351,0.007214599,0.0002148777,0.001143229,0.00134407,0.001475047,0.0418368],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001557737,"about_ca_system_score_gemma":0.002037577,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03088028,"about_ca_topic_score_gemma":0.03468821,"domain_scores_codex":[0.9977204,0.0004108751,0.0005893467,0.0006316282,0.000381971,0.0002656746],"domain_scores_gemma":[0.9960287,0.0007590364,0.0008749763,0.0005602658,0.001512036,0.000265145],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.0004789927,0.00008032461,0.05165654,0.002396784,0.0003177036,0.00009728812,0.0000919153,0.0004875964,0.00009082071,0.001147083,0.9254915,0.01766353],"study_design_scores_gemma":[0.0006878441,0.0001370481,0.1917582,0.002924231,0.0004176061,0.0006494341,0.0005737503,0.001217126,0.0003442891,0.002273306,0.7988951,0.000121974],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.001763976,0.0004488934,0.0001570107,0.000177054,0.00004977974,0.0000775994,0.9939771,0.00009350041,0.003255056],"genre_scores_gemma":[0.006636649,0.0007723426,0.0004867839,0.0002991319,0.0000705274,0.0006469256,0.9876017,0.00005935611,0.003426598],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.06473944,"threshold_uncertainty_score":0.216575,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04458149741048512,"score_gpt":0.4668608787198441,"score_spread":0.4222793813093589,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}